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Blind Source Separation for Non-stationary Signal Based on Time-Frequency Analysis

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3 Author(s)
Shi He-Ping ; Tianjin Eng. Center for Fieldbus Control Technol., Tianjin Univ. of Technol. & Educ. Tianjin, Tianjin, China ; Cao Ji-Hua ; Liu Xiao

To separate independent sources from the linear mixed observed data, the traditional blind source separation (BSS) is usually neglected the non-stationary of the signals. With the non-stationary of the signals focused on, a new blind source separation algorithm is proposed by combining the characteristic of time-frequency analysis (TFA) and blind source separation (BSS). In the algorithm, the full time-frequency domain Wigner searching is utilized to find the local maximum of the Smoothed Pseudo Wigner-Ville time-frequency distribution. The simulations show this algorithm not only suppresses cross term interference but also remain time-frequency resolutions. The proposed algorithm provides an effective technology for fault diagnosis of mechanical equipment.

Published in:

Intelligent Networks and Intelligent Systems (ICINIS), 2011 4th International Conference on

Date of Conference:

1-3 Nov. 2011

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